Sustainability Indicators: Relevance, Public Policy Support and Challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sustainability is a topic that has gained importance in several fields of knowledge, including the public, private and society spheres, based on the discussions that involve the definition of several public policies. Sustainability Indicators (SI) are metrics that seek to measure the level of sustainability and compile information for better decision-making concerning policies, programs, projects and actions related to sustainability. Demonstrated their relevance to public policies the SI appears as an essential tool for evaluating development goals as a sustainable proposal. In this way, this research aimed to discuss the main challenges and methodological limitations found in the use of SI, emphasizing the main fragilities identified in the literature. In methodological terms, the research has exploratory characteristics, supported by the mixed methods approach using a theoretical-empirical analysis, from the available literature on the subject and the methodologies used and the experience of researchers about the topic addressed. The main results demonstrated that Sustainability Indicators are tools that should be used to define, implement, evaluate and monitor public policies at all levels, considering the potentialities/weaknesses and priorities of each context.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it